How can I interpret the evaluation results for my regression model?

For regression models, the evaluation results are based on the following metrics or measures:

• Mean Absolute Error: it tells you how close the predictions are to the actual outcomes.
• Mean Squared Error: it is like absolute error, but it will give a little more weight to the large errors.
• R Squared: it tells you how much better the model’s prediction is than just predicting the mean target value all the time.